PROCESS OPTIMIZATION AND AUTOMATION IN E-COMMERCE BUSINESS OPERATION

Mister Sandman is an ecommerce start-up company located in the heart of Berlin, Germany. It is an online mattress & bedding company, selling products both on their own as well as 17 other marketplaces across Europe. I have successfully completed 6 months of my internship with the company. It was really an amazing experience here to work and learn. This journey has been very informative, interesting, and important on all scales. I was entrusted with various projects and tasks and actively worked on data collection, cleaning, manipulation, preprocessing, visualization, analysis, and automation of various tasks in the company's ecommerce platform and marketplaces. In the beginning, I was trained to understand the end to end working mechanism of day to day operations. My goals and areas of contribution were precisely put forward to me which empowered me with focus and clear vision. I then utilized my knowledge from the university and past experience of work at Amazon to support them in an efficient way. I made an analysis on Pricing, Rebate, Shipping, Ratings & Reviews, Inventories, Visibility, Orders & Sales and worked on to optimize and automate the process using various techniques of python skills. I also learnt and used other technical skills and languages to execute the tasks along with Python such as SQL, Macros, Tableau and Power BI tools depending on the requirements. I also make different reports for the orders & sales - weekly and monthly using various analysis and visualization tools and contributed to understand the development and improvement areas for the business to grow and continue serving our customers the best way.Mister Sandman is an ecommerce start-up company located in the heart of Berlin, Germany. It is an online mattress & bedding company, selling products both on their own as well as 17 other marketplaces across Europe. I have successfully completed 6 months of my internship with the company. It was really an amazing experience here to work and learn. This journey has been very informative, interesting, and important on all scales. I was entrusted with various projects and tasks and actively worked on data collection, cleaning, manipulation, preprocessing, visualization, analysis, and automation of various tasks in the company's ecommerce platform and marketplaces. In the beginning, I was trained to understand the end to end working mechanism of day to day operations. My goals and areas of contribution were precisely put forward to me which empowered me with focus and clear vision. I then utilized my knowledge from the university and past experience of work at Amazon to support them in an efficient way. I made an analysis on Pricing, Rebate, Shipping, Ratings & Reviews, Inventories, Visibility, Orders & Sales and worked on to optimize and automate the process using various techniques of python skills. I also learnt and used other technical skills and languages to execute the tasks along with Python such as SQL, Macros, Tableau and Power BI tools depending on the requirements. I also make different reports for the orders & sales - weekly and monthly using various analysis and visualization tools and contributed to understand the development and improvement areas for the business to grow and continue serving our customers the best way

Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches

Search engine bias: the structuration of traffic on the World-Wide Web

Search engines are essential components of the World Wide Web; both commercially and in terms of everyday usage, their importance is hard to overstate. This thesis examines the question of why there is bias in search engine results – bias that invites users to click on links to large websites, commercial websites, websites based in certain countries, and websites written in certain languages. In this thesis, the historical development of the search engine industry is traced. Search engines first emerged as prototypical technological startups emanating from Silicon Valley, followed by the acquisition of search engine companies by major US media corporations and their development into portals. The subsequent development of pay-per-click advertising is central to the current industry structure, an oligarchy of virtually integrated companies managing networks of syndicated advertising and traffic distribution. The study also shows a global landscape in which search production is concentrated in and caters for large global advertising markets, leaving the rest of the world with patchy and uneven search results coverage. The analysis of interviews with senior search engine engineers indicates that issues of quality are addressed in terms of customer service and relevance in their discourse, while the analysis of documents, interviews with search marketers, and participant observation within a search engine marketing firm showed that producers and marketers had complex relationships that combine aspects of collaboration, competition, and indifference. The results of the study offer a basis for the synthesis of insights of the political economy of media and communication and the social studies of technology tradition, emphasising the importance of culture in constructing and maintaining both local structures and wider systems. In the case of search engines, the evidence indicates that the culture of the technological entrepreneur is very effective in creating a new megabusiness, but less successful in encouraging a debate on issues of the public good or public responsibility as they relate to the search engine industry

Composite web search

The figure above shows Google’s results page for the query “taylor swift”, captured in March 2016. Assembled around the long-established list of search results is content extracted from various source — news items and tweets merged within the results ranking, images, songs and social media profiles displayed to the right of the ranking, in an interface element that is known as an entity card. Indeed, the entire page seems more like an assembly of content extracted from various sources, rather than just a ranked list of blue links. Search engine result pages have become increasingly diverse over the past few years, with most commercial web search providers responding to user queries with different types of results, merged within a unified page. The primary reason for this diversity on the results page is that the web itself has become more diverse, given the ease with which creating and hosting different types of content on the web is possible today. This thesis investigates the aggregation of web search results retrieved from various document sources (e.g., images, tweets, Wiki pages) within information “objects” to be integrated in the results page assembled in response to user queries. We use the terms “composite objects” or “composite results” to refer to such objects, and throughout this thesis use the terminology of Composite Web Search (e.g., result composition) to distinguish our approach from other methods of aggregating diverse content within a unified results page (e.g., Aggregated Search). In our definition, the aspects that differentiate composite information objects from aggregated search blocks are that composite objects (i) contain results from multiple sources of information, (ii) are specific to a common topic or facet of a topic rather than a grouping of results of the same type, and (iii) are not a uniform ranking of results ordered only by their topical relevance to a query. The most widely used type of composite result in web search today is the entity card. Entity cards have become extremely popular over the past few years, with some informal studies suggesting that entity cards are now shown on the majority of result pages generated by Google. As composite results are used more and more by commercial search engines to address information needs directly on the results page, understanding the properties of such objects and their influence on searchers is an essential aspect of modern web search science. The work presented throughout this thesis attempts the task of studying composite objects by exploring users’ perspectives on accessing and aggregating diverse content manually, by analysing the effect composite objects have on search behaviour and perceived workload, and by investigating different approaches to constructing such objects from diverse results. Overall, our experimental findings suggest that items which play a central role within composite objects are decisive in determining their usefulness, and that the overall properties of composite objects (i.e., relevance, diversity and coherence) play a combined role in mediating object usefulness

Large-Scale Indexing, Discovery, and Ranking for the Internet of Things (IoT)

Network-enabled sensing and actuation devices are key enablers to connect real-world objects to the cyber world. The Internet of Things (IoT) consists of the network-enabled devices and communication technologies that allow connectivity and integration of physical objects (Things) into the digital world (Internet). Enormous amounts of dynamic IoT data are collected from Internet-connected devices. IoT data are usually multi-variant streams that are heterogeneous, sporadic, multi-modal, and spatio-temporal. IoT data can be disseminated with different granularities and have diverse structures, types, and qualities. Dealing with the data deluge from heterogeneous IoT resources and services imposes new challenges on indexing, discovery, and ranking mechanisms that will allow building applications that require on-line access and retrieval of ad-hoc IoT data. However, the existing IoT data indexing and discovery approaches are complex or centralised, which hinders their scalability. The primary objective of this article is to provide a holistic overview of the state-of-the-art on indexing, discovery, and ranking of IoT data. The article aims to pave the way for researchers to design, develop, implement, and evaluate techniques and approaches for on-line large-scale distributed IoT applications and services

Lexical innovation on the web and social media

This dissertation investigates the emergence and diffusion of English neologisms on the web and social media, employing a data-driven methodology to identify a substantial sample of 851 neologisms. Neologisms are examined from their coining to successful dissemination within the community, with the study revealing a wide spectrum of degrees of diffusion. The exploration extends to studying the usage and diffusion of selected neologisms on the web and on Twitter, with a particular focus on social dynamics and variation among different speaker groups. Moreover, the dissertation probes into semantic innovation, demonstrating substantial socio-semantic variation and polarized public discourse surrounding certain neologisms. The research conducts an extensive analysis of semantic innovation and socio-semantic variation, elucidating significant socio-semantic discrepancies between various communities. The dissertation sheds light on the social and semantic dynamics underpinning the life cycle of neologisms within a linguistically diverse community

Flexible Integration and Efficient Analysis of Multidimensional Datasets from the Web

If numeric data from the Web are brought together, natural scientists can compare climate measurements with estimations, financial analysts can evaluate companies based on balance sheets and daily stock market values, and citizens can explore the GDP per capita from several data sources. However, heterogeneities and size of data remain a problem. This work presents methods to query a uniform view - the Global Cube - of available datasets from the Web and builds on Linked Data query approaches

Intuitive interaction: Steps towards an integral understanding of the user experience in interaction design

A critical review of traditional practices and methodologies demonstrates an underplaying of firstly the role of emotions and secondly aspects of exploration in interaction behaviour in favour of a goal orientated focus in the user experience (UX). Consequently, the UX is a commodity that can be designed, measured, and predicted. An integral understanding of the UX attempts to overcome the rationalistic and instrumental mindset of traditional Human-Computer Interaction (HCI) on several levels. Firstly, the thesis seeks to complement a functional view of interaction with a qualitative one that considers the complexity of emotions. Emotions are at the heart of engagement and connect action irreversibly to the moment it occurs; they are intettwined with cognition, and decision making. Furthermore, they introduce the vague and ambiguous aspects of experience and open it up to potentiality of creation. Secondly, the thesis examines the relationship between purposive and non-purposive user behaviour such as exploration, play and discovery. The integral position proposed here stresses the procedurally relational nature and complexity of interaction experience. This requires revisiting and augmenting key themes of HCI practice such as interactivity and intuitive design. Intuition is investigated as an early and unconscious form of learning, and unstructured browsing discussed as random interaction mechanisms as forms of implicit learning. Interactivity here is the space for user's actions, contributions and creativity, not only in the design process but also during interaction as co-authors of their experiences. Finally, I envisage integral forms of usability methods to embrace the vague and the ambiguous, in order to enrich HCI's vocabulary and design potential. Key readings that inform this position cut across contemporary philosophy, media and interaction studies and professional HCI literature. On a practical level, a series of experimental interaction designs for web-browsing aim to augment the user's experience, and create space for user's intuition

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions